This paper surveys domain-specific architectures (DSAs) built from two emerging memory technologies. Hybrid memory cube (HMC) and high bandwidth memory (HBM) can reduce data movement between memory and computation by placing computing logic inside memory dies. On the other hand, the emerging non-volatile memory, metal-oxide resistive random access memory (ReRAM) has been considered as a promising candidate for future memory architecture due to its high density, fast read access and low leakage power. The key feature is ReRAM’s capability to perform the inherently parallel in-situ matrix-vector multiplication in the analog domain. We focus on the DSAs for two important applications—graph processing and machine learning acceleration. Based on the understanding of the recent architectures and our research experience, we also discuss several potential research directions.

本文调查了基于两种新兴内存技术构建的领域特定架构（DSA）。混合存储多维数据集（HMC）和高带宽内存（HBM）可通过将计算逻辑放置在内存管芯内来减少内存与计算之间的数据移动。另一方面，新兴的非易失性存储器，金属氧化物电阻随机存取存储器（ReRAM）由于其高密度，快速读取访问和低泄漏功率而被认为是未来存储器体系结构的有希望的候选者。ReRAM的主要功能是在模拟域中执行固有并行原位矩阵矢量乘法的能力。我们专注于两个重要应用程序的DSA：图形处理和机器学习加速。基于对最新架构的了解和我们的研究经验，